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Estimation with Applications to Tracking and Navigation

Estimation with Applications to Tracking and Navigation Author Yaakov Bar-Shalom
ISBN-10 9780471465218
Release 2004-04-05
Pages 584
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Expert coverage of the design and implementation of state estimation algorithms for tracking and navigation Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a balanced combination of linear systems, probability, and statistics. The authors provide a review of the necessary background mathematical techniques and offer an overview of the basic concepts in estimation. They then provide detailed treatments of all the major issues in estimation with a focus on applying these techniques to real systems. Other features include: Problems that apply theoretical material to real-world applications In-depth coverage of the Interacting Multiple Model (IMM) estimator Companion DynaEst(TM) software for MATLAB(TM) implementation of Kalman filters and IMM estimators Design guidelines for tracking filters Suitable for graduate engineering students and engineers working in remote sensors and tracking, Estimation with Applications to Tracking and Navigation provides expert coverage of this important area.



Estimation with Applications to Tracking and Navigation

Estimation with Applications to Tracking and Navigation Author Yaakov Bar-Shalom
ISBN-10 9780471465218
Release 2004-04-05
Pages 584
Download Link Click Here

Expert coverage of the design and implementation of state estimation algorithms for tracking and navigation Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a balanced combination of linear systems, probability, and statistics. The authors provide a review of the necessary background mathematical techniques and offer an overview of the basic concepts in estimation. They then provide detailed treatments of all the major issues in estimation with a focus on applying these techniques to real systems. Other features include: Problems that apply theoretical material to real-world applications In-depth coverage of the Interacting Multiple Model (IMM) estimator Companion DynaEst(TM) software for MATLAB(TM) implementation of Kalman filters and IMM estimators Design guidelines for tracking filters Suitable for graduate engineering students and engineers working in remote sensors and tracking, Estimation with Applications to Tracking and Navigation provides expert coverage of this important area.



Estimation with Applications to Tracking and Navigation

Estimation with Applications to Tracking and Navigation Author Yaakov Bar-Shalom
ISBN-10 047141655X
Release 2001-06-25
Pages 584
Download Link Click Here

Expert coverage of the design and implementation of state estimation algorithms for tracking and navigation Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a balanced combination of linear systems, probability, and statistics. The authors provide a review of the necessary background mathematical techniques and offer an overview of the basic concepts in estimation. They then provide detailed treatments of all the major issues in estimation with a focus on applying these techniques to real systems. Other features include: Problems that apply theoretical material to real-world applications In-depth coverage of the Interacting Multiple Model (IMM) estimator Companion DynaEst(TM) software for MATLAB(TM) implementation of Kalman filters and IMM estimators Design guidelines for tracking filters Suitable for graduate engineering students and engineers working in remote sensors and tracking, Estimation with Applications to Tracking and Navigation provides expert coverage of this important area.



Estimation with Applications to Tracking and Navigation

Estimation with Applications to Tracking and Navigation Author Yaakov Bar-Shalom
ISBN-10 OCLC:1025222980
Release 2001
Pages 558
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Estimation with Applications to Tracking and Navigation has been writing in one form or another for most of life. You can find so many inspiration from Estimation with Applications to Tracking and Navigation also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Estimation with Applications to Tracking and Navigation book for free.



Tracking and Data Association

Tracking and Data Association Author Yaakov Bar-Shalom
ISBN-10 UOM:39015013064426
Release 1988
Pages 353
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In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation; methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; and methods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory. As a result, the book represents a blend of new methods in general computational analysis, and specific, but also generic, techniques for study of systems theory ant its particular branches, such as optimal filtering and information compression. - Best operator approximation, - Non-Lagrange interpolation, - Generic Karhunen-Loeve transform - Generalised low-rank matrix approximation - Optimal data compression - Optimal nonlinear filtering



Multitarget multisensor Tracking

Multitarget multisensor Tracking Author Yaakov Bar-Shalom
ISBN-10 0890065179
Release 1992-01
Pages 442
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Compiles the latest techniques for those who design advanced systems for tracking, surveillance and navigation. This second volume expands upon the first with 11 new chapters. The text includes pertinent contributions from leading international experts in this field.



Bayesian Estimation and Tracking

Bayesian Estimation and Tracking Author Anton J. Haug
ISBN-10 9781118287804
Release 2012-05-29
Pages 448
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A practical approach to estimating and tracking dynamic systems in real-worl applications Much of the literature on performing estimation for non-Gaussian systems is short on practical methodology, while Gaussian methods often lack a cohesive derivation. Bayesian Estimation and Tracking addresses the gap in the field on both accounts, providing readers with a comprehensive overview of methods for estimating both linear and nonlinear dynamic systems driven by Gaussian and non-Gaussian noices. Featuring a unified approach to Bayesian estimation and tracking, the book emphasizes the derivation of all tracking algorithms within a Bayesian framework and describes effective numerical methods for evaluating density-weighted integrals, including linear and nonlinear Kalman filters for Gaussian-weighted integrals and particle filters for non-Gaussian cases. The author first emphasizes detailed derivations from first principles of eeach estimation method and goes on to use illustrative and detailed step-by-step instructions for each method that makes coding of the tracking filter simple and easy to understand. Case studies are employed to showcase applications of the discussed topics. In addition, the book supplies block diagrams for each algorithm, allowing readers to develop their own MATLAB® toolbox of estimation methods. Bayesian Estimation and Tracking is an excellent book for courses on estimation and tracking methods at the graduate level. The book also serves as a valuable reference for research scientists, mathematicians, and engineers seeking a deeper understanding of the topics.



Advanced Kalman Filtering Least Squares and Modeling

Advanced Kalman Filtering  Least Squares and Modeling Author Bruce P. Gibbs
ISBN-10 9781118003169
Release 2011-03-29
Pages 640
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This book is intended primarily as a handbook for engineers who must design practical systems. Its primary goal is to discuss model development in sufficient detail so that the reader may design an estimator that meets all application requirements and is robust to modeling assumptions. Since it is sometimes difficult to a priori determine the best model structure, use of exploratory data analysis to define model structure is discussed. Methods for deciding on the “best” model are also presented. A second goal is to present little known extensions of least squares estimation or Kalman filtering that provide guidance on model structure and parameters, or make the estimator more robust to changes in real-world behavior. A third goal is discussion of implementation issues that make the estimator more accurate or efficient, or that make it flexible so that model alternatives can be easily compared. The fourth goal is to provide the designer/analyst with guidance in evaluating estimator performance and in determining/correcting problems. The final goal is to provide a subroutine library that simplifies implementation, and flexible general purpose high-level drivers that allow both easy analysis of alternative models and access to extensions of the basic filtering. Supplemental materials and up-to-date errata are downloadable at http://booksupport.wiley.com.



Multisensor Attitude Estimation

Multisensor Attitude Estimation Author Hassen Fourati
ISBN-10 9781315351759
Release 2016-11-03
Pages 606
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There has been an increasing interest in multi-disciplinary research on multisensor attitude estimation technology driven by its versatility and diverse areas of application, such as sensor networks, robotics, navigation, video, biomedicine, etc. Attitude estimation consists of the determination of rigid bodies’ orientation in 3D space. This research area is a multilevel, multifaceted process handling the automatic association, correlation, estimation, and combination of data and information from several sources. Data fusion for attitude estimation is motivated by several issues and problems, such as data imperfection, data multi-modality, data dimensionality, processing framework, etc. While many of these problems have been identified and heavily investigated, no single data fusion algorithm is capable of addressing all the aforementioned challenges. The variety of methods in the literature focus on a subset of these issues to solve, which would be determined based on the application in hand. Historically, the problem of attitude estimation has been introduced by Grace Wahba in 1965 within the estimate of satellite attitude and aerospace applications. This book intends to provide the reader with both a generic and comprehensive view of contemporary data fusion methodologies for attitude estimation, as well as the most recent researches and novel advances on multisensor attitude estimation task. It explores the design of algorithms and architectures, benefits, and challenging aspects, as well as a broad array of disciplines, including: navigation, robotics, biomedicine, motion analysis, etc. A number of issues that make data fusion for attitude estimation a challenging task, and which will be discussed through the different chapters of the book, are related to: 1) The nature of sensors and information sources (accelerometer, gyroscope, magnetometer, GPS, inclinometer, etc.); 2) The computational ability at the sensors; 3) The theoretical developments and convergence proofs; 4) The system architecture, computational resources, fusion level.



Kalman Filtering

Kalman Filtering Author Charles K. Chui
ISBN-10 9783662026663
Release 2013-06-29
Pages 195
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In addition to making a number of minor corrections and updat ing the references, we have expanded the section on "real-time system identification" in Chapter 10 of the first edition into two sections and combined it with Chapter 8. In its place, a very brief introduction to wavelet analysis is included in Chapter 10. Although the pyramid algorithms for wavelet decompositions and reconstructions are quite different from the Kalman filtering al gorithms, they can also be applied to time-domain filtering, and it is hoped that splines and wavelets can be incorporated with Kalman filtering in the near future. College Station and Houston Charles K. Chui September 1990 Guanrong Chen Preface to the First Edition Kalman filtering is an optimal state estimation process applied to a dynamic system that involves random perturbations. More precisely, the Kalman filter gives a linear, unbiased, and min imum error variance recursive algorithm to optimally estimate the unknown state of a dynamic system from noisy data taken at discrete real-time. It has been widely used in many areas of industrial and government applications such as video and laser tracking systems, satellite navigation, ballistic missile trajectory estimation, radar, and fire control. With the recent development of high-speed computers, the Kalman filter has become more use ful even for very complicated real-time applications.



Applied State Estimation and Association

Applied State Estimation and Association Author Chaw-Bing Chang
ISBN-10 9780262335065
Release 2016-07-08
Pages 472
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Applied state estimation and association is an important area for practicing engineers in aerospace, electronics, and defense industries, used in such tasks as signal processing, tracking, and navigation. This book offers a rigorous introduction to both theory and application of state estimation and association. It takes a unified approach to problem formulation and solution development that helps students and junior engineers build a sound theoretical foundation for their work and develop skills and tools for practical applications. Chapters 1 through 6 focus on solving the problem of estimation with a single sensor observing a single object, and cover such topics as parameter estimation, state estimation for linear and nonlinear systems, and multiple model estimation algorithms. Chapters 7 through 10 expand the discussion to consider multiple sensors and multiple objects. The book can be used in a first-year graduate course in control or system engineering or as a reference for professionals. Each chapter ends with problems that will help readers to develop derivation skills that can be applied to new problems and to build computer models that offer a useful set of tools for problem solving. Readers must be familiar with state-variable representation of systems and basic probability theory including random and stochastic processes.



Fundamentals of Object Tracking

Fundamentals of Object Tracking Author Sudha Challa
ISBN-10 9780521876285
Release 2011-07-28
Pages 375
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Introduces object tracking algorithms from a unified, recursive Bayesian perspective, along with performance bounds and illustrative examples.



An Introduction to Kalman Filtering with MATLAB Examples

An Introduction to Kalman Filtering with MATLAB Examples Author Narayan Kovvali
ISBN-10 9781627051408
Release 2013-09-01
Pages 81
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The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a variety of applications, e.g., target tracking, guidance and navigation, and communications systems. The purpose of this book is to present a brief introduction to Kalman filtering. The theoretical framework of the Kalman filter is first presented, followed by examples showing its use in practical applications. Extensions of the method to nonlinear problems and distributed applications are discussed. A software implementation of the algorithm in the MATLAB programming language is provided, as well as MATLAB code for several example applications discussed in the manuscript.



Kalman Filtering

Kalman Filtering Author Mohinder S. Grewal
ISBN-10 9781118984963
Release 2015-02-02
Pages 640
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The definitive textbook and professional reference on Kalman Filtering – fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.



Estimation and Tracking

Estimation and Tracking Author Yaakov Bar-Shalom
ISBN-10 096483121X
Release 1998
Pages 536
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Estimation and Tracking has been writing in one form or another for most of life. You can find so many inspiration from Estimation and Tracking also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Estimation and Tracking book for free.



Probability Random Signals and Statistics

Probability  Random Signals  and Statistics Author X. Rong Li
ISBN-10 9781351421515
Release 2017-12-14
Pages 472
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With this innovative text, the study-and teaching- of probability and random signals becomes simpler, more streamlined, and more effective. Its unique "textgraph" format makes it both student-friendly and instructor-friendly. Pages with a larger typeface form a concise text for basic topics and make ideal transparencies; pages with smaller type provide more detailed explanations and more advanced material.



Advances in Estimation Navigation and Spacecraft Control

Advances in Estimation  Navigation  and Spacecraft Control Author Daniel Choukroun
ISBN-10 9783662447857
Release 2015-01-02
Pages 550
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This book presents selected papers of the Itzhack Y. Bar-Itzhack Memorial Sympo- sium on Estimation, Navigation, and Spacecraft Control. Itzhack Y. Bar-Itzhack, professor Emeritus of Aerospace Engineering at the Technion – Israel Institute of Technology, was a prominent and world-renowned member of the applied estimation, navigation, and spacecraft attitude determination communities. He touched the lives of many. He had a love for life, an incredible sense of humor, and wisdom that he shared freely with everyone he met. To honor Professor Bar-Itzhack's memory, as well as his numerous seminal professional achievements, an international symposium was held in Haifa, Israel, on October 14–17, 2012, under the auspices of the Faculty of Aerospace Engineering at the Technion and the Israeli Association for Automatic Control. The book contains 27 selected, revised, and edited contributed chapters written by eminent international experts. The book is organized in three parts: (1) Estimation, (2) Navigation and (3) Spacecraft Guidance, Navigation and Control. The volume was prepared as a reference for research scientists and practicing engineers from academy and industry in the fields of estimation, navigation, and spacecraft GN&C.